SOCI44915: Statistics in Health and Medicine with R

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• To help students understand the meaning of selected statistics that are widely used in official health reports, the media, and academic publications.
• To introduce selected statistical methods that are widely used in academic research on health and medicine so that they understand the logic of each method and when it could be used appropriately.
• To offer initial training to students on how to use R and RStudio to enable them to conduct simple yet useful analyses on real-world data with the methods learnt.

• Lecture Topics:
• Introduction: why statistics and statistical methods are important and useful in research on health and medicine; how data about health and medicine are collected; sources of data; overview of the module
• Measuring health and illness
• Statistics of healthcare and health expenditure
• Risks, odds, and odds ratios
• Probability and probability distributions
• Descriptive vs. inferential statistics of one health statistic
• Comparing groups on health and healthcare
• Analysing associations between two variables
• Non-parametric statistical tests
• Review and advice on assessment
• Topics for Comuputer Sessions:
• Introduction to R and RStudio; preparing data for analysis
• Producing and understanding statistics and graphs for one variable
• Producing and understanding statistics and graphs for two variables
• Examining statistical distributions
• Testing hypothesis and constructing confidence intervals
• Conducting non-parametric statistical tests
• Analysing associations between quantitative variables
• Analysing associations between categorical variables
• Producing and analysing odds ratio and relative risks
• Review and help with assessment.

Subject-specific Knowledge:

• Understanding the logic and the specific principles of a range of statistical methods and tools widely used in academic research on health and medicine;
• Detailed knowledge and critical understanding of basic but important principles for using statistics in a variety of contexts related to health and medicine;
• Understanding the nature and production of different types of data and how it affects the subsequent analyses of the data;
• Knowledge of different methods and the conditions for their appropriate use;
• Understanding the meaning of descriptive vs. inferential statistics;
• Understanding the meaning of parametric vs. non-parametric statistics;
• Understanding the meaning of probability, risk, odds, odds ratios, probability distributions and other related concepts.

Subject-specific Skills:

• Capabilities for managing research, including collecting and analysing data, conducting and disseminating research in such a way that is consistent with both professional practice and principles of research ethics and risk assessment;
• Interpretation of statistics derived from a particular method;
• Ability to prepare large scale data for missing values;
• Ability to evaluate the relative pros and cons of each specific concept, measure or method in the context of health and medical research;
• Ability to produce simple statistics and interpret their meaning in relation to the substantive meaning and context of health and medicine;
• Ability to critically review other researchers work in light of statistical reasoning in health and medical research;
• Ability to compare groups in terms of a particular health measure;
• Ability to use R and RStudio for producing desired statistics;
• Ability to conduct replicable research.

Key Skills:

• KS1 - The ability to evaluate and synthesize information obtained from a variety of sources (written, electronic, oral, visual); to communicate relevant information in a variety of ways and to select the most appropriate means of communication relative to the specific task. Students will also be able to communicate their own formulations in a clear and accessible way; they will be able to respond effectively to others and to reflect on and monitor the use of their communication skills;
• KS2 - The ability to read and interpret complex tables, graphs, and diagrams; to organize, classify and interpret numerical and logical data; to make inferences from sets of data; to use advanced techniques of data analysis; and to appreciate the scope and applicability of numerical and logical data;
• KS3 - Competence in using information technology to use a computer software package effectively; to use effective information storage and retrieval; and to use web-based resources;
• KS5 - Effective time-management, working to prescribed deadlines;
• KS6 - The ability to engage in different forms of learning, to seek and to use feedback from both peers and academic staff, and to monitor and critically reflect on the learning process.

• Lectures: introduce and explain the meaning of key concepts and the logic of each method, illustrating with examples
• Computer practical sessions: introduce the widely used and powerful statistical programme R and its user-friendly environment RStudio; demonstrate how each method covered in the lectures is applied with R; explain the meaning of the outputs; enable students to use the methods and computing programmes to conduct their own analyses.
• Summative assessment: with a 3000-word essay, students are provided with the opportunity to apply the methods learnt for analysing real-world data; conduct independent research project on any health-related issue of their interest.
• Formative Assessment: with a 500-word outline, students have the option to produce a plan for their summative work, including their research focus, the data to be analysed, the methods to be used, and the expected results; they will receive feedbacks from the module convenor which will help keep them on track and enhance the quality of their summative work.

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